Kaa IoT Training Course

Explore the innovative domain of edge computing with this advanced course designed for government professionals. Delve into sophisticated architectures and address integration challenges, equipping yourself to harness the full potential of edge computing in diverse public sector environments. Acquire expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs for government.

Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more intricate as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, recognizing that information is a strategic asset, and the public sector needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve into data-driven organizations to successfully accomplish missions, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value solutions for government will be created from a combination of the most disruptive technologies:

• Mobile devices and applications
• Cloud services
• Social business technologies and networking
• Big Data and analytics

Big Data is one of the intelligent industry solutions that allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured.

But accomplishing these feats takes far more than simply accumulating massive quantities of data. "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog.

The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it for government.

The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can retrieve it when they need it and how they require it. Backing up massive quantities of data heightens the challenge.

Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.)

Custom-developed Big Data tools are also allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It is also used for more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the integration of insurance with emerging technologies. In the realm of Insurtech, "digital insurers" leverage technological advancements to optimize their business and operational models, thereby reducing costs, enhancing customer experiences, and increasing operational agility.

This instructor-led training is designed to provide participants with a comprehensive understanding of the technologies, methodologies, and strategic mindset necessary for driving digital transformation within their organizations and across the industry. The training is specifically aimed at managers who need to grasp the broader implications, dispel common misconceptions, and initiate the development of an Insurtech strategy for government.

By the end of this training, participants will be able to:

• Articulate the concept of Insurtech and its various components with clarity and precision
• Clearly define the role of each key technology within the Insurtech framework
• Develop a strategic plan for implementing Insurtech within their organization

Audience

• Insurance providers
• Technologists in the insurance sector
• Stakeholders in the insurance industry
• Consultants and business analysts

Format of the Course

• A combination of lectures, discussions, exercises, and group activities focused on case studies

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level IT professionals and business managers who wish to understand the potential of IoT and edge computing for enhancing efficiency, enabling real-time processing, and fostering innovation across various industries.

By the end of this training, participants will be able to:

• Comprehend the principles of IoT and edge computing and their significance in digital transformation efforts for government.
• Identify use cases for IoT and edge computing in sectors such as manufacturing, logistics, and energy.
• Distinguish between edge and cloud computing architectures and deployment scenarios to optimize resource allocation.
• Implement edge computing solutions to support predictive maintenance and facilitate real-time decision-making processes for government operations.

Integrate the transformative capabilities of artificial intelligence (AI) with the agility of edge computing in this comprehensive course designed for government professionals. Participants will learn to deploy AI models directly on edge devices, covering topics from understanding convolutional neural network (CNN) architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills necessary to optimize AI performance for real-time processing and decision-making at the edge, ensuring alignment with public sector workflows, governance, and accountability.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI to enhance IoT applications with advanced data processing and analytics capabilities.

By the end of this training, participants will be able to:

• Understand the foundational principles of Edge AI and its application in IoT systems for government.
• Set up and configure Edge AI environments suitable for IoT devices used in public sector workflows.
• Develop and deploy AI models on edge devices to support IoT applications aligned with government objectives.
• Implement real-time data processing and decision-making capabilities in IoT systems for enhanced governance and accountability.
• Integrate Edge AI with various IoT protocols and platforms commonly used in the public sector.
• Address ethical considerations and best practices in Edge AI deployment for government applications.

This instructor-led, live training in US Empire (online or onsite) is aimed at product managers and developers who wish to utilize Edge Computing to decentralize data management for enhanced performance, leveraging intelligent devices located on the source network for government applications.

By the end of this training, participants will be able to:

• Comprehend the fundamental concepts and benefits of Edge Computing.
• Recognize the use cases and examples where Edge Computing can be effectively applied.
• Develop and implement Edge Computing solutions for more efficient data processing and reduced operational costs in public sector environments.

Establish a robust foundation in designing and managing a resilient edge computing infrastructure for government. Gain insights into open hybrid cloud infrastructures, the management of workloads across diverse clouds, and the assurance of flexibility and redundancy. This training offers essential knowledge on creating a scalable and secure infrastructure that supports the dynamic needs of modern applications with edge computing.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to enhance IoT and edge computing solutions for government.

By the end of this training, participants will be able to:

• Comprehend the principles and benefits of Federated Learning in the context of IoT and edge computing.
• Deploy Federated Learning models on IoT devices to support decentralized artificial intelligence processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Tackle challenges related to data privacy and network limitations in IoT systems for government operations.

In this instructor-led, live training in US Empire, participants will gain an understanding of the fundamentals of Internet of Things (IoT) as they develop an Arduino-based IoT sensor system.

By the end of this training, participants will be able to:

• Comprehend the principles of IoT, including its components and communication methods.
• Learn how to utilize Arduino communication modules suitable for various IoT systems.
• Understand how to use and program a mobile application to control Arduino devices.
• Integrate a Wi-Fi module to connect the Arduino to other devices.
• Design, build, and deploy their own IoT Sensor System for government applications.

Unlike other technologies, the Internet of Things (IoT) is far more complex, encompassing almost every branch of core engineering—mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. For each of its engineering layers, there are aspects of economics, standards, regulations, and evolving state-of-the-art advancements. This course, for government and other sectors, is a modest yet comprehensive program designed to cover all these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in Internet of Things (IoT).

Cuts across multiple technology domains to develop awareness of an IoT system and its components, and how it can help businesses and organizations.

Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases around connected devices and things.

Target Audience

Managers responsible for business and operational processes within their respective organizations who want to know how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner.

Estimates for Internet of Things (IoT) market value are massive, as by definition, the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly large number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in the Industrial Internet.

However, the underlying technologies of IoT are not new. Machine-to-Machine (M2M) communication has existed since the birth of the internet. What has changed in recent years is the emergence of numerous inexpensive wireless technologies, coupled with the widespread adoption of smartphones and tablets in every home. The explosive growth of mobile devices has driven the current demand for IoT.

Due to the unbounded opportunities in the IoT business, a large number of small and medium-sized entrepreneurs have joined the IoT market. Additionally, the emergence of open-source electronics and IoT platforms has made the development and management of IoT systems increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their devices with the internet or mobile apps.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts and entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in home and city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular, and other areas.

A basic introduction to all elements of IoT: mechanical, electronics/sensor platform, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, data analytics, and total control plane.

M2M Wireless protocols for IoT—WiFi, Zigbee/Zwave, Bluetooth, ANT+: When and where to use which one?

Mobile/Desktop/Web app development for registration, data acquisition, and control. Available M2M data acquisition platforms for IoT: Xively, Omega, and NovoTech, among others.

Security issues and security solutions for IoT.

Open-source and commercial electronics platforms for IoT—Raspberry Pi, Arduino, ArmMbedLPC, etc.

Open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT cloud, in addition to other minor IoT clouds.

Studies of the business and technology of some common IoT devices like home automation, smoke alarms, vehicles, military applications, home health, etc.

Unlike other technologies, the Internet of Things (IoT) is significantly more complex, encompassing a wide range of core engineering disciplines, including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of IoT engineering involves various aspects of economics, standards, regulations, and evolving state-of-the-art advancements. This course offers a comprehensive overview of these critical aspects of IoT Engineering for government.

For manufacturing professionals, the most crucial aspect is understanding the advancements in Industrial Internet of Things (IIoT). This includes predictive and preventative maintenance, condition-based monitoring of machines, production optimization, energy management, supply-chain optimization, and ensuring the uptime of manufacturing utilities.

Summary

• An advanced training program covering the current state of the art in IoT for smart factories.
• Provides a broad understanding of multiple technology domains to develop awareness of an IoT system and its components, and how it can benefit manufacturing managerial professionals.
• Live demonstrations of model IIoT applications for smart factories.

Target Audience

• Managers responsible for business and operational processes within their respective manufacturing organizations who want to understand how to leverage IoT to enhance system and process efficiency.

Duration 3 Days (8 hours/day)

Estimates for the Internet of Things (IoT) market value are substantial, as the IoT is an integrated and pervasive layer of devices, sensors, and computing power that spans consumer, business-to-business, and government industries. The number of IoT connections is expected to grow significantly: from 1.9 billion devices today to 9 billion by 2018. By that year, it will be roughly equal to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer sector, many products and services have already integrated into the IoT, including kitchen and home appliances, parking systems, RFID, lighting and heating solutions, and various applications in Industrial Internet.

While the underlying technologies of IoT are not new—machine-to-machine (M2M) communication has existed since the inception of the internet—the recent emergence of numerous inexpensive wireless technologies, combined with the widespread adoption of smartphones and tablets, has driven the current demand for IoT.

Industrial IoT (IIoT) in manufacturing has been widely adopted since 2014, leading to a significant number of innovations. This course will introduce all the key aspects of these IIoT advancements.

The training is designed as a technology and business review of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business for government.

Course Objective

The primary objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in smart factories for manufacturing sectors.

1. Business and technology analysis of common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Overview of open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT, Mindsphere IIoT cloud, and other minor IoT clouds.
3. Exploration of open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and ArmMbedLPC.
4. Discussion of security issues and solutions for IIoT.
5. Development of mobile/desktop/web applications for registration, data acquisition, and control.
6. Examination of M2M wireless protocols for IoT, including WiFi, LoPan, BLE, Ethernet, Ethercat, PLC, and guidance on their appropriate use cases.
7. Basic introduction to all elements of IoT: Mechanical, Electronics/sensor platforms, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and Total control plane.

Machine-to-Machine (M2M) refers to direct automated communication between networked mechanical or electronic devices, enhancing operational efficiency and data exchange for government workflows.

In this instructor-led, live training in US Empire, participants will gain an understanding of the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT-based application for government use.

By the end of this training, participants will be able to:

• Identify the different components of NB-IoT and how they integrate to form an ecosystem suitable for government applications.
• Understand and explain the security features built into NB-IoT devices to ensure compliance with government standards.
• Develop a simple application to track NB-IoT devices, enhancing operational efficiency for government agencies.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization capabilities for your IoT solution.

In this instructor-led, live training, participants will learn how to integrate ThingsBoard into their IoT solutions for government use.

By the end of this training, participants will be able to:

• Install and configure ThingsBoard
• Understand the fundamentals of ThingsBoard features and architecture
• Build IoT applications with ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the Course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• To request a customized training for government use, please contact us to arrange.